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G-Hensley
by G-Hensley

Get Learning Roadmap

get_learning_roadmap

Retrieve learning roadmap sections including current focus, queue, backlog, on hold, and completed.

Instructions

Get learning roadmap with current focus, queue, and completed learning

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sectionNoSpecific section to retrieve (defaults to all)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes

Implementation Reference

  • api/mcp.ts:379-415 (registration)
    Registration of the 'get_learning_roadmap' tool with the MCP server, including input schema and handler.
    // Tool: Get Learning Roadmap
    server.registerTool(
      "get_learning_roadmap",
      {
        title: "Get Learning Roadmap",
        description: "Get learning roadmap with current focus, queue, and completed learning",
        inputSchema: {
          section: z.enum(["current_focus", "queue", "backlog", "on_hold", "completed"]).optional().describe("Specific section to retrieve (defaults to all)"),
        },
        outputSchema: textContentOutputSchema,
      },
      async ({ section }) => {
        const result: Record<string, unknown> = {};
    
        if (!section || section !== "completed") {
          try {
            const roadmap = await readJsonFile<LearningRoadmapData>("learning/roadmap.json");
            if (section) {
              result[section] = roadmap[section as keyof LearningRoadmapData];
            } else {
              result.roadmap = roadmap;
            }
          } catch {
            // File may not exist
          }
        }
        if (!section || section === "completed") {
          try {
            const completed = await readJsonFile<CompletedLearningData>("learning/completed.json");
            result.completed = completed.entries;
          } catch {
            // File may not exist
          }
        }
        return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
      }
    );
  • Handler function that fetches learning roadmap data (current_focus, queue, backlog, on_hold) from 'learning/roadmap.json' and completed learning from 'learning/completed.json' via GitHub raw content, returning JSON.
    async ({ section }) => {
      const result: Record<string, unknown> = {};
    
      if (!section || section !== "completed") {
        try {
          const roadmap = await readJsonFile<LearningRoadmapData>("learning/roadmap.json");
          if (section) {
            result[section] = roadmap[section as keyof LearningRoadmapData];
          } else {
            result.roadmap = roadmap;
          }
        } catch {
          // File may not exist
        }
      }
      if (!section || section === "completed") {
        try {
          const completed = await readJsonFile<CompletedLearningData>("learning/completed.json");
          result.completed = completed.entries;
        } catch {
          // File may not exist
        }
      }
      return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
    }
  • Input schema: optional 'section' parameter of type enum (current_focus, queue, backlog, on_hold, completed).
    inputSchema: {
      section: z.enum(["current_focus", "queue", "backlog", "on_hold", "completed"]).optional().describe("Specific section to retrieve (defaults to all)"),
    },
  • The readJsonFile generic helper used to fetch and parse JSON data from GitHub raw content.
    async function readJsonFile<T>(relativePath: string): Promise<T> {
      const content = await fetchFromGitHub(relativePath);
      return JSON.parse(content) as T;
    }
  • Type definition for LearningRoadmapData with current_focus, queue, backlog, and on_hold arrays of LearningItem.
    export interface LearningRoadmapData {
      current_focus: LearningItem[];
      queue: LearningItem[];
      backlog: LearningItem[];
      on_hold: LearningItem[];
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fails to disclose behavioral traits like read-only nature, authentication requirements, or side effects. It simply describes the output without any behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise (one sentence) and front-loads the action. However, it omits useful details like the optional parameter and default behavior, making it slightly under-informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description does not need to detail return values. However, it lacks context about the optional parameter and how it affects the result, leaving some gaps for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the parameter is well-documented in the schema. The description adds no additional meaning beyond listing sections, meeting the baseline but not enhancing it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it retrieves a learning roadmap with specific sections (current focus, queue, completed learning), distinguishing it from siblings like 'get_skills' or 'get_education'. However, it does not mention that an optional 'section' parameter can filter results.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as 'get_skills' or 'update_learning_progress'. There is no mention of prerequisites, context, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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